Evidence map›Paper›PMID 35252172›Full record

ArticleFrontiers in cell and developmental biology2022

Deciphering Cell-Type-Specific Gene Expression Signatures of Cardiac Diseases Through Reconstruction of Bulk Transcriptomes.

Xiaobin Wu, Xingyu Zhao, Yufei Xiong, Ming Zheng, Chao Zhong, Yuan Zhou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine.International journal of molecular sciences · 2026
    Review
  2. Transcriptome studies of inherited dilated cardiomyopathies.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Xiaobin WuDepartment of Biomedical Informatics, Center for Noncoding RNA Medicine, School of Basic Medical Sciences, Peking University, Beijing, China.
Xingyu ZhaoBeijing Key Laboratory of Tumor Systems Biology, Department of Immunology, School of Basic Medical Sciences, Institute of Systems Biomedicine, Peking University, Beijing, China.
Yufei XiongMOE Key Laboratory of Molecular Cardiovascular Sciences, Peking University, Beijing, China.
Ming ZhengMOE Key Laboratory of Molecular Cardiovascular Sciences, Peking University, Beijing, China.
Chao ZhongBeijing Key Laboratory of Tumor Systems Biology, Department of Immunology, School of Basic Medical Sciences, Institute of Systems Biomedicine, Peking University, Beijing, China.
Yuan ZhouDepartment of Biomedical Informatics, Center for Noncoding RNA Medicine, School of Basic Medical Sciences, Peking University, Beijing, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac diseases compose a fatal disease category worldwide. Over the past decade, high-throughput transcriptome sequencing of bulk heart tissues has widened our understanding of the onset and progression of cardiac diseases. The recent rise of single-cell RNA sequencing (scRNA-seq) technology further enables deep explorations of their molecular mechanisms in a cell-type-specific manner. However, due to technical difficulties in performing scRNA-seq on heart tissues, there are still few scRNA-seq studies on cardiac diseases. In this study, we demonstrate that an effective alternative could be cell-type-specific computational reconstruction of bulk transcriptomes. An integrative bulk transcriptome dataset covering 110 samples from 12 studies was first constructed by re-analysis of raw sequencing data derived from the heart tissues of four common cardiac disease mouse models (myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy). Based on the single-cell reference covering four major cardiac component cell types and 22 immune cell subtypes, for each sample, the bulk transcriptome was reconstructed into cellular compositions and cell-type-specific expression profiles by CIBERSORTx. Variations in the estimated cell composition revealed elevated abundances of fibroblast and monocyte during myocardial infarction, which were further verified by our flow cytometry experiment. Moreover, through cell-type-specific differential gene expression and pathway enrichment analysis, we observed a series of signaling pathways that mapped to specific cell type in diseases, like MAPK and EGFR1 signaling pathways in fibroblasts in myocardial infarction. We also found an increased expression of several secretory proteins in monocytes which may serve as regulatory factors in cardiac fibrosis. Finally, a ligand-receptor analysis identified key cell types which may serve as hubs in cellular communication in cardiac diseases. Our results provide novel clues for the cell-type-specific signatures of cardiac diseases that would promote better understanding of their pathophysiological mechanisms.

Indexed as

cardiac diseasescellular compositionfibroblastmonocytesingle-cell RNA sequencingtranscriptome reconstruction

Identifiers

PMID35252172
PMCPMC8894713
OpenAlexW4212941918

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.